Hu Sheng-Qi, Hu Jian-Nan, Chen Ru-Dong, Yu Jia-Sheng
Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Department of Respiratory and Critical Care Medicine, Key Laboratory of Pulmonary Diseases of Health Ministry, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Front Neurol. 2022 Dec 6;13:1034313. doi: 10.3389/fneur.2022.1034313. eCollection 2022.
To identify risk factors for hospital-acquired pneumonia (HAP) in patients with aneurysmal subarachnoid hemorrhage (aSAH) and establish a predictive model to aid evaluation.
The cohorts of 253 aSAH patients were divided into the HAP group ( = 64) and the non-HAP group ( = 189). Univariate and multivariate logistic regression were performed to identify risk factors. A logistic model (Model-Logit) was established based on the independent risk factors. We used risk factor categories to develop a model (Model-Cat). Receiver operating characteristic curves were generated to determine the cutoff values. Areas under the curves (AUCs) were calculated to assess the accuracy of models and single factors. The Delong test was performed to compare the AUCs.
The multivariate logistic analysis showed that the age [ = 0.012, odds ratio (OR) = 1.059, confidence interval (CI) = 1.013-1.107], blood glucose (BG; >7.22 mmol/L; = 0.011, OR = 2.781, CI = 1.263-6.119), red blood distribution width standard deviation (RDW-SD; = 0.024, OR = 1.118, CI = 1.015-1.231), and Glasgow coma scale (GCS; < 0.001, OR = 0.710, CI = 0.633-0.798) were independent risk factors. The Model-Logit was as follows: Logit() = -5.467 + 0.057 Age + 1.023 BG (>7.22 mmol/L, yes = 1, no = 0) + 0.111 RDW-SD-0.342 GCS. The AUCs values of the Model-Logit, GCS, age, BG (>7.22 mmol/L), and RDW-SD were 0.865, 0.819, 0.634, 0.698, and 0.625, respectively. For clinical use, the Model-Cat was established. In the Model-Cat, the AUCs for GCS, age, BG, and RDW-SD were 0.850, 0.760, 0.700, 0.641, and 0.564, respectively. The AUCs of the Model-Logit were insignificantly higher than the Model-Cat (Delong test, = 0.157). The total points from -3 to 4 and 5 to 14 were classified as low- and high-risk levels, respectively.
Age, BG (> 7.22 mmol/L), GCS, and RDW-SD were independent risk factors for HAP in aSAH patients. The Model-Cat was convenient for practical evaluation. The aSAH patients with total points from 5 to 14 had a high risk for HAP, suggesting the need for more attention during treatment.
确定动脉瘤性蛛网膜下腔出血(aSAH)患者医院获得性肺炎(HAP)的危险因素,并建立一个预测模型以辅助评估。
将253例aSAH患者队列分为HAP组(n = 64)和非HAP组(n = 189)。进行单因素和多因素逻辑回归以确定危险因素。基于独立危险因素建立逻辑模型(模型-Logit)。我们使用危险因素类别建立一个模型(模型-Cat)。生成受试者工作特征曲线以确定临界值。计算曲线下面积(AUC)以评估模型和单个因素的准确性。进行德龙检验以比较AUC。
多因素逻辑分析显示,年龄(P = 0.012,比值比[OR] = 1.059,置信区间[CI] = 1.013 - 1.107)、血糖(BG;>7.22 mmol/L;P = 0.011,OR = 2.781,CI = 1.263 - 6.119)、红细胞分布宽度标准差(RDW-SD;P = 0.024,OR = 1.118,CI = 1.015 - 1.231)和格拉斯哥昏迷量表(GCS;P < 0.001,OR = 0.710,CI = 0.633 - 0.798)是独立危险因素。模型-Logit如下:Logit(P)= -5.467 + 0.057×年龄 + 1.023×BG(>7.22 mmol/L,是 = 1,否 = 0)+ 0.111×RDW-SD - 0.342×GCS。模型-Logit、GCS、年龄、BG(>7.22 mmol/L)和RDW-SD的AUC值分别为0.865、0.819、0.634、0.698和0.625。为便于临床应用,建立了模型-Cat。在模型-Cat中,GCS、年龄、BG和RDW-SD的AUC分别为0.850、0.760、0.700、0.641和0.564。模型-Logit的AUC略高于模型-Cat(德龙检验,P = 0.157)。总积分-3至4分和5至14分分别归类为低风险和高风险水平。
年龄、BG(>7.22 mmol/L)、GCS和RDW-SD是aSAH患者发生HAP的独立危险因素。模型-Cat便于实际评估。总积分5至14分的aSAH患者发生HAP的风险较高,提示治疗期间需要更多关注。